How Election Cycles Influence Automation Adoption: A Comparative Study of Public and Private Sector Policies in the U.S

This dataset examines how U.S. electoral cycles influence automation adoption trends in the public and private sectors. Drawing on a mixed-method approach, the data combine longitudinal quantitative analysis of automation rates over the period 2000–2020 with qualitative insights from semi-structured interviews with 30 decision-makers. Significant increases in public sector automation are seen after the election, given the policy for modernization by an incoming administration, while private sector investments in automation are much lower during the pre-election period due to uncertainty over future regulations. The current study fills an important gap between political economy and technological adoption by providing empirical evidence and practical recommendations for policymakers and business executives. These drivers include regulatory uncertainty and an electoral mandate; a dataset on the trends, regression analyses, and thematic insights was drawn upon.本数据集旨在探究美国选举周期对公共与私营部门自动化应用趋势的影响。本研究采用混合研究范式，整合了2000年至2020年间自动化应用率的纵向定量分析结果，以及针对30名决策人员开展的半结构化访谈所获质性洞察。研究显示，在新一届政府推出现代化施政政策后，公共部门的自动化应用水平出现显著提升；而受未来监管政策不确定性影响，私营部门在选举前的自动化投资规模显著偏低。本研究通过为政策制定者与企业高管提供实证依据与实践建议，填补了政治经济学领域与技术应用研究之间的重要研究空白。影响自动化应用的核心驱动因素包括监管不确定性与选举授权；本数据集涵盖了相关趋势数据、回归分析结果以及主题性洞察内容。